Learning-based approaches [1]}, [2]}, [3]}, [4]}, [5]} attempt to learn the ISP, and how to reverse it, in an end-to-end manner.
CycleISP [2]} uses a 2-branch model to learn the RAW2RGB and RGB2RAW transformations. InvISP [3]} models the camera ISP as an invertible function using normalizing-flows [8]}. These learned methods are essentially non-interpretable black-boxes. MBISPLD [4]} proposes a novel learnable, invertible and interpretable model-based ISP, based on classical designs [10]}, [11]}.
In a more complex domain, Arad et al.  proposed the the recovery of whole-scene hyperspectral (HS) information from a RGB image [12]}.
